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Sobre

Sobre

J. T. Saraiva nasceu no Porto, Portugal, em 1962 e obteve um grau equivalente a MSc, o PhD e o título de Agregado pela Faculdade de Engenharia da Universidade do Porto em 1987, 1993 e 2002 onde é actualmente Professor. Intergra o INESC Porto desde 1985 onde é Investigador Sénior e colaborou ou foi responsável por diversas actividades no âmbito de projectos financiados pela EU, projectos financiandos por entidades nacionais bem diversos contratos de consultoria técnica por exemplo envolvendo a Entidade Reguladora dos Serviços Energéticos, a EDP Distribuição, a EDP Produção, a REN, a Empresa de Electricidade da Madeira, a Empresa de Electricidade dos Açores e os Operadores do Ssitema Eléctrico Grego e Brasileiro. Ao longo da sua carreira académica orientou mais de 50 Teses de Mestrado, 10 teses de Doutoramento e foi co-autor de 3 livros, de mais de 30 publicações em international journals e mais de 120 publicações em conferências internacionais.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    João Tomé Saraiva
  • Cluster

    Energia
  • Cargo

    Investigador Coordenador
  • Desde

    15 julho 1985
026
Publicações

2022

Functional model of residential consumption elasticity under dynamic tariffs

Autores
Ganesan, K; Saraiva, JT; Bessa, RJ;

Publicação
ENERGY AND BUILDINGS

Abstract
One of the major barriers for the retailers is to understand the consumption elasticity they can expect from their contracted demand response (DR) clients. The current trend of DR products provided by retailers are not consumer-specific, which poses additional barriers for the active engagement of consumers in these programs. The elasticity of consumers' demand behavior varies from individual to individual. The utility will benefit from knowing more accurately how changes in its prices will modify the consumption pattern of its clients. This work proposes a functional model for the consumption elasticity of the DR contracted consumers. The model aims to determine the load adjustment the DR consumers can provide to the retailers or utilities for different price levels. The proposed model uses a Bayesian probabilistic approach to identify the actual load adjustment an individual contracted client can provide for different price levels it can experience. The developed framework provides the retailers or utilities with a tool to obtain crucial information on how an individual consumer will respond to different price levels. This approach is able to quantify the likelihood with which the consumer reacts to a DR signal and identify the actual load adjustment an individual contracted DR client provides for different price levels they can experience. This information can be used to maximize the control and reliability of the services the retailer or utility can offer to the System Operators. (c) 2021 Published by Elsevier B.V.

2022

Concept and design of a Real Time Walrasian Local Electricity Market

Autores
Mello, J; Villar, J; Saraiva, JT;

Publicação
International Conference on the European Energy Market, EEM

Abstract
This paper proposes a real time Walrasian based market design for local electricity trading, considering the roles of the different players, the settlement procedures, and the necessary balance responsibilities with the wholesale market under collective self-consumption rules. A Walrasian mechanism based on consecutive auctions for very short delivery periods is proposed, where the auctioneer defines a price for each of these delivery periods to which peers react by generating and consuming accordingly and informing if they trade with the auctioneer or with their retailer or aggregator. This market has no energy purchase contracts, and energy is billed based on each peer's generation or consumption for each delivery period with the price defined by the auctioneer. © 2022 IEEE.

2021

A two-stage constructive heuristic algorithm to handle integer investment variables in transmission network expansion planning

Autores
Oliveira, ED; Junior, ICS; de Oliveira, LW; de Mendonca, IM; Vilaca, P; Saraiva, JT;

Publicação
ELECTRIC POWER SYSTEMS RESEARCH

Abstract
Due to the complexity and great relevance of the transmission network expansion planning (TNEP) for electrical systems, this topic remains on the focus of the academic and industry communities. Therefore, this paper proposes a new approach to deal efficiently with the basic formulation of this problem, combining low computational effort and good quality of the obtained solutions. In this approach four factors contribute to solve TNEP problem more efficiently: (i) the investment decisions are selected using a new Constructive Heuristic Algorithm (CHA); (ii) the proposed CHA includes two stages, using the relaxation of the decision integers variables through the hyperbolic tangent function and the setting of its function's slope; (iii) the performance index that was adopted was modified regarding what was reported in the literature; (iv) the use of the primal-dual interior point optimization technique allows the representation of the nonlinearities in the problem: transmission power losses and the hyperbolic tangent function (investment decision). The quality and effectiveness of the proposed algorithm is verified using two real power systems, where the proposed CHA is able to lead to better quality solutions than the ones reported in the literature.

2021

Electricity Cost of Green Hydrogen Generation in the Iberian Electricity Market

Autores
De Oliveira, AR; Collado, JV; Saraiva, JT; Domenech, S; Campos, FA;

Publicação
2021 IEEE MADRID POWERTECH

Abstract

2021

Detection and Mitigation of Extreme Losses in Distribution Networks

Autores
Paulos, JP; Fidalgo, JN; Saraiva, JT; Barbosa, N;

Publicação
2021 IEEE MADRID POWERTECH

Abstract

Teses
supervisionadas

2021

Estimativa do Impacto da PRE no Custo de Produção de Energia Elétrica em 2019

Autor
Maria Carolina de Magalhães Bastos

Instituição
UP-FEUP

2021

Previsão de preços de mercado baseada em Deep Learning

Autor
Ana Rita Martins Cruz e Silva

Instituição
UP-FEUP

2021

Multi-Modal Tasking for Skin Lesion Classi cation using DNN

Autor
Rafaela Garrido Ribeiro de Carvalho

Instituição
UP-FEUP

2021

Simulation of Hydro Power Plants in Electricity Markets Using an Agent-Based Model

Autor
José Carlos Vieira Sousa

Instituição
UP-FEUP

2021

Wireless optical fibre sensors network for the health monitoring of concrete structures

Autor
Pedro Miguel Madeira da Silva

Instituição